Software Engineer

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Job Description

As a platform software engineer, you will be responsible for designing and implementing software to easily deploy and deliver the machine and deep learning assets developed by ML engineers as scalable web APIs. You will also be responsible for the code reviews of your team members and providing guidance.

The platform product strategy is determined by team discussions based on the feedback from the platform users and input from other stakeholders. You will be expected to contribute to the team decision from the viewpoint of a software engineer.

You are someone who is:

• Interested in the implementation of machine learning technologies for the sake of solving social issues


• Interested in cutting edge computer science technologies


• Good at software development in a team environment

Responsibilities

• Development experience utilizing AWS or other cloud platforms


• Practical experience in SRE and system operation


• Experience in software development projects


• Experience with source control management systems (SCM) and CI/CD


• Effective interpersonal and communication skills (Business-level English and conversational Japanese OR Business-level Japanese and at least reading and writing capabilities for English)

Qualifications

• Experience designing and implementing scalable processing infrastructure utilizing distributed processing infrastructure (Kubernetes/Hadoop, etc.)


• Background in computer science or a related field


• Project management skills


• Product and service development experience


• Experience working in a startup environment


• Understanding of machine learning frameworks (Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow/Keras/PyTorch)


• Understanding of machine learning models in a business environment (linear regression, ensemble learning, boosting, RNN, CNN, GCN, GAN, etc.)


• Strong initiative in a business setting to lead a team/organization

About ExaWizards

ExaWizards is an AI start-up with a simple mission: solve social issues using AI and create a happy society. But to achieve it, they’re tackling issues across a wide variety of industries: Care tech, HR, fintech, medicine, security, and more. They believe AI can help solve problems in all these areas, and they’re determined to do just that. Their business model can be broken into two different flows: project-focused and product-focused. For project-focused initiatives, they start from scratch. Their ML engineers and consultants identify business problems and build models aimed at solving them. In their product flow, they take the ML models developed for specific problems and generalize them to be useful for a wider array of problems. Normally they develop these solutions into SaaS products.